code: def test_ablation_flip_max_ablations(self):
      ex = {"sentence": "this movie is terrible"}
      ex_tokens = self.ablation_flip.tokenize(ex["sentence"])
      self.classification_config[ablation_flip.NUM_EXAMPLES_KEY] = 1
      self.classification_config[ablation_flip.MAX_ABLATIONS_KEY] = 1
      self.classification_config[ablation_flip.FIELDS_TO_ABLATE_KEY] = [
          "sentence"
      ]
      cfs = self.ablation_flip.generate(
          ex,
          self.classification_model,
          None,
          self.classification_config,
      )
      cf_tokens = self.ablation_flip.tokenize(list(cfs)[0]["sentence"])
      self.assertLen(cf_tokens, len(ex_tokens) - 1)
  
      ex = {"sentence": "this long movie is terrible and horrible."}
      self.classification_config[ablation_flip.NUM_EXAMPLES_KEY] = 1
      self.classification_config[ablation_flip.MAX_ABLATIONS_KEY] = 1
      self.classification_config[ablation_flip.FIELDS_TO_ABLATE_KEY] = [
          "sentence"
      ]
      cfs = self.ablation_flip.generate(
          ex,
          self.classification_model,
          None,
          self.classification_config,
      )
      self.assertEmpty(cfs)
  
imports: from collections.abc import Iterable, Iterator
  from absl.testing import absltest
  from lit_nlp.api import types
  from lit_nlp.components import ablation_flip
  from lit_nlp.examples.models import glue_models
  import numpy
  from lit_nlp.lib import file_cache
label_desc: Use image node_id 7 for calling the ModelBasedAblationFlipTest obj's underlying member method code with example usage: obj.test_ablation_flip_max_ablations() without return types